19 citations · 45 across the 11 of their papers we have counts for
4 papers · 1 filter
A Unified Framework for Sparse Relaxed Regularized Regression: SR3
Peng Zheng, Travis Askham, Steven L. Brunton +2
Regularized regression problems are ubiquitous in statistical modeling, signal processing, and machine learning. Sparse regression in particular has been instrumental in scientific…
Learning Nonlinear Brain Dynamics: van der Pol Meets LSTM
German Abrevaya, Irina Rish, Aleksandr Y. Aravkin +7
Many real-world data sets, especially in biology, are produced by complex nonlinear dynamical systems. In this paper, we focus on brain calcium imaging (CaI) of different organisms…
Learning Robust Representations for Computer Vision
Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy +1
Unsupervised learning techniques in computer vision often require learning latent representations, such as low-dimensional linear and non-linear subspaces. Noise and outliers in th…
Estimating Shape Parameters of Piecewise Linear-Quadratic Problems
Peng Zheng, Aleksandr Y. Aravkin, Karthikeyan Natesan Ramamurthy
Piecewise Linear-Quadratic (PLQ) penalties are widely used to develop models in statistical inference, signal processing, and machine learning. Common examples of PLQ penalties inc…